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Record W2047949588 · doi:10.1080/14742837.2010.493658

‘We've Also Become Quite Good Friends’: Environmentalists, Social Networks and Social Comparison in British Columbia, Canada

2010· article· en· W2047949588 on OpenAlexaffabout
Mark C. J. Stoddart, David B. Tindall

Bibliographic record

VenueSocial movement studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of British ColumbiaMemorial University of Newfoundland
Fundersnot available
KeywordsFriendshipInterpersonal tiesEnvironmental movementSocial movementGovernment (linguistics)Social network (sociolinguistics)Social engagementPoliticsSociologyPublic relationsPower (physics)Political sciencePolitical economySocial mediaSocial scienceLaw

Abstract

fetched live from OpenAlex

Social networks influence social movement recruitment and individuals' ongoing participation in social movement organizations. In this article, we use a qualitative approach to explore the meaning of social networks for environmental movement participants in British Columbia, Canada. Our analysis draws on interviews with 33 core members of the movement. Environmental group participation creates multiplex social networks, encompassing work, leisure and friendship. Social movement networks are conduits for information exchange among environmental groups and they amplify the political power of individual participants. Ties to government workers and forest company management are more intense – based on frequency of contact – than ties to forestry labour or First Nations groups. However, forestry workers and First Nations are viewed more positively than government or forest company management. This illustrates how the intensity of social network ties can be distinguished from the subjective meanings attached to them by network participants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0320.008
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.278
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations71
Published2010
Admission routes2
Has abstractyes

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